This is part of a series looking for reasons for the Oilers Corsi% collapse in 2012-13 by examining things on a shift-by-shift basis. Part 1 can be found here.
In the first part of this series, I examined the performance of Oilers forwards in 2012-13 through three distinct lenses: the percentage of shifts on which they allowed a shot attempt against (SAA), the percentage of shifts with an SAA that turned into multi-SAA shifts and the percentage of shifts that were multi-SAA shifts. I did this in order to try and gain an understanding of how, at a shift-by-shift level, the performance of the Oilers forwards changed in 2012-13. Today, I’m going to examine the defencemen through this lens.
First up is looking at the defencemen on the basis of the number of shifts with an SAA recorded. I’ll start with the guys who appeared both this year and last year.
This graph is sorted, from left to right, by the size of the increase in the number of shifts with an SAA. If you’re Ryan Whitney’s agent, looking for a selling point, you can quite fairly say “When the Oilers defencemen went to hell last year in terms of shifts with an SAA, Whitney experienced the smallest growth in that number amongst anyone who took a regular shift!” Unfortunately, he was still really bad at this, just like he was in 2011-12. It’s just that other guys got worse.
The Petry/Smid change really catches the eye. Those fellows were a pairing for most of the year – about 78% of Petry’s time on the ice at 5v5 was with Smid and about 81% of Smid’s 5v5 time was with Petry. There seemed to be a consensus that these guys weren’t as good this year as they were last year and this data would seem to provide some explanation for why people might have come to that conclusion. I’m not convinced that that’s true, but we’ll come to it.
Potter experienced a rise in his percentage of shifts with an SAA this year. RELATED: Potter played more frequently with Whitney this year than he did last year. He had horrible numbers with him this year, just like he did last year.
Nick Schultz, who played about 67% of his Oiler time in 2011-12 with Ryan Whitney, also saw a slight increase in his volume of shifts with an SAA this year, despite hardly playing Whitney. Why might that be? Well, let’s look at the numbers for the guys who weren’t on the Oilers for both seasons.
Oh dear. Justin Schultz. It’s not perfectly clear but he saw at least a single SAA on 49.2% of his shifts in 2012-13. That’s an awful number. I hate to complain about things that are past but there might be a valuable lesson here about whether or not planning for a rookie defenceman to be in your top four when you’re a marginal playoff contender is a good idea. Fistric’s number is 44.3%, which isn’t great but, as with Potter, he shows significant Whitney effects.
With no further comment, I note that Tom Gilbert doesn’t appear to have been such a bad performer in retrospect.
Let’s switch lenses here and look at how the defencemen performed in terms shifts with at least one SAA that turned into multiple-SAA shifts. Again, the theory here is pretty straightforward: if you’re going to be on the ice for an SAA, you’d rather nip it in the bud, recover the puck and get out of the zone instead of continuing to be trapped in your zone while the opposition tees off. Again, I’ve sorted the graph from left to right, from biggest decrease to biggest increase.
Welp. Not much for Ryan Whitney’s agent in this. In addition to continuing to be awful in terms of the percentage of shifts on which he experienced an SAA, he saw a rather large increase in his percentage of multi-SAA shifts. He was more likely than any non-Justin Schultz defenceman to be on the ice for a shift on which there was an SAA and he was the most likely of any of the defencemen to be on the ice for a multi-SAA shift.
Petry and Smid jump out to me again. Way back in the day, Vic Ferrari made a fine point about defencemen who subsequently turned up in the All-Star game being more likely to have been given away at some point in their career. The canonical example of this is Larry Murphy, booed off a crappy team in Toronto, who went on to play just fine for a Stanley Cup champion in Detroit. It’s difficult to reconcile.
One theory as to why this might be is that defencemen don’t have a ton of control over certain aspects of their results. If you’re on a team that spends a lot of time in its own end because it can’t generate opportunities at the other end of the ice, you’re going to look bad. Spending a lot of time in your own end of the ice is like hanging out in a bad part of town – the more time you spend there, the more likely it is that something bad will happen.
You’ll recall that I pointed out above that Petry and Smid were more likely to be on the ice for a shift on which there was an SAA this year. I kind of theorized that the increased frequency with which this happened might explain why people thought that they looked poor – they were hanging out in a bad part of town. I find it awfully fascinating that the frequency with which those shifts turned into multi-SAA shifts didn’t really change from 2011-12 to 2012-13.
In Petry’s case, it went up very slightly – from 40.2% to 40.3%. Effectively, he performed exactly the same as he did last year – 209 of his 518 shifts with at least one SAA were multi-SAA shifts. If he’d performed exactly the same as last year, it would be 208.5. It’s eerily similar. In Smid’s case, 196 of his 521 shifts with at least one SAA were multi-SAA shifts. If he’d posted the same percentage as last year (36.8% in 2011-12; 37.6% in 2012-13), he’d have had 191.5 multi-SAA shifts. To put that into perspective, it’s one extra shift that turns from a single SAA shift to a multi-SAA shift per 10.7 games.
To underline this: Smid/Petry produced virtually identical performances in 2011-12 and 2012-13 once you limit the analysis to those shifts on which there was an SAA. To the extent that their defensive performance declined, it was in the volume of shifts on which there was an SAA, not the volume of multi-SAA shifts. This gives rise to a question, I think: to what extent do we attribute blame for that failing to Smid/Petry and to what extent is it due to things that were happening elsewhere?
Corey Potter and Nick Schultz experienced moves in opposite directions with their percentages of multi-SAA shifts. In both cases, I think we can find some explanation of this in the data for guys who were new to the team this year.
Mark Fistric and Justin Schultz were at opposite ends of the spectrum this year. Justin had shifts on which he allowed at least one SAA turn into multi-SAA shifts 42.1% of the time, the second worst percentage on the team. Fistric had a 35.3% number, which was the best on the team. Interestingly with Fistric, the Fistric/Potter pairing actually posted really good numbers this year – they were north of 50% as a Corsi%. The sample is small, they were a third pairing but that certainly wasn’t part of the problem for the OIlers.
As far as Nick Schultz’s increase in his multi-SAA%, playing a lot with Justin probably didn’t help him. Justin was awfully weak at this; notably weaker than Whitney was last year. Again – it sure would have been nice if the Oilers had kind of planned for the rookie coming out of college to start in a third pairing role at 5v5 but c’est la vie.
Let’s flip lenses again and look at multi-SAA shifts as a percentage of all shifts. As I mentioned in the last post, this sort of blends the ideas in the first two lenses. I tend to think it’s a bit less useful but, as they say, it is what is.
I think I’ve set out above what, specifically, accounts for the increases in these numbers this year. Petry and Smid saw a greater share of their shifts lead to at least one SAA, while maintaining their multi-SAA number when you look only at shifts on which there was at least one SAA. Nick Schultz met Justin and things did not go that well defensively. (Probably noteworthy: Nick Schultz posted a better Corsi% when he wasn’t playing with Justin than when he was. If I had to guess, I’d guess that it had to do with Justin’s apparent weakness at preventing SAA and multi-SAA shifts.) Potter basically came out of things as a wash, a mix of playing with the guy with the worst numbers (Whitney) and the best (Fistric). For all the praise that Justin Schultz is getting – I think he’s going to finish ahead of Yakupov in Calder voting – he doesn’t show particularly well in these numbers.
I want to talk a little about the idea of finding individual metrics that matter. Ultimately, what the people who are interested in analytics are doing, or trying to do, is find metrics that tell us about the individual who is on the ice. The objection of the “Hockey isn’t baseball” people is overstated in my opinion, but there’s merit to it. Every time a hockey player is on the ice, there are eleven other guys busy polluting his numbers. Right now, we try to infer whether or not a guy is contributing by looking at his top line underlying numbers, like Corsi% and then looking for things that might make us think that that’s not an adequate reflection of his numbers – maybe he’s getting really good or really poor ZoneStarts, or maybe he’s got strong/weak teammates. It’s alright as far as it goes – I tend to think it’s a decent way of looking at things – but it’s an awfully subjective sort of thing.
What we really need to do is figure out how to isolate the things that a player does or doesn’t do that drive the Corsi%. That’s the trick. Thinking about defencemen this way strikes me as having some possibilities there. I’m not entirely convinced that defencemen are able to exercise a great deal of control over the number of shifts that they play on which the other team gets possession and is able to attack. If you play with Ryan O’Reilly, the puck’s going to be in the other end of the ice more than if you play with an NHL team foolish enough to give me minutes at centre ice.
In that circumstance, you’d be the same guy, but the volume of shifts on which you sustained at least one SAA is going to be much higher, because I can’t keep the puck in the other end of the ice like Ryan O’Reilly can. If we think about this in terms of identifying a metric, what we really need is something that measures a defenceman’s performance during the opportunities that he does have to prevent a shift with an SAA from occurring. Keeping the play in the offensive zone once it’s there, to the limited extent that defencemen can do that. Breaking up plays that are coming towards your end of the ice before they result in an SAA. Turning the puck back around. When that sort of information and data starts to become available, I think we’re going to start seeing really good individual metrics for defencemen get developed.
That’s kind of why I find looking at multi-SAA shifts/SAA shifts so interesting. We’re kind of starting everyone from a similar starting point there – we know that there’s been an SAA and then seeing how well they stop the bleeding. I would expect that the influence of the wings is less there than it is with the percentage of shifts with an SAA, because you’re kind of cutting out the impact of a forward line that just keeps things at the other end of the ice. You are, quite possibly, distilling more of the influence of the two defencemen and the centre, in terms of recovering the puck and getting out of the defensive zone. I don’t deny that the wingers are involved in that, I only suggest that the weighting of the involvement as between the five players on the ice isn’t 20/20/20/20/20. At the very least, I’d suggest that the relative weighting of the defencemen’s influence on that is greater than on the issue of whether or not a puck stays in the offensive zone.
I wasn’t surprised to see that the Oilers’ pairing which was together last year and this year (Petry/Smid) essentially posted the same numbers at this. Armed with the knowledge of who the two worst Oiler defencemen were at preventing SAA and multi-SAA shifts, it’s probably unsurprising to find that Whitney and Justin Schultz were such an atrocious pairing. They played 120:06 together at 5v5 – two entire hockey games! – and posted an incredible 36.3% Corsi%. 36.3%! It’s just…wow.
Up next, I’ll turn my attention towards the other end of the ice and SAF.Email Tyler Dellow at firstname.lastname@example.org